嚮量微積分、綫性代數和微分形式

嚮量微積分、綫性代數和微分形式 下載 mobi epub pdf 電子書 2025

John H.Hubbard
圖書標籤:
想要找書就要到 圖書大百科
立刻按 ctrl+D收藏本頁
你會得到大驚喜!!
PREFACE
CHAPTER 0 PRELIMINARIES
0.0 Introduction
0.1 Reading mathematics
0.2 Quantifiers and negation
0.3 Set theory
0.4 Functions
0.5 Real numbers
0.6 Infinite sets
0.7 Complex numbers
CHAPTER 1 VECTORS, MATRICES, AND DERIVATIVES
1.0 Introduction
1.1 Introducing the actors: points and vectors
1.2 Introducing the actors: matrices
1.3 Matrix multiplication as a linear transformation
1.4 The geometry of Rn
1.5 Limits and continuity
1.6 Four big theorems
1.7 Derivatives in several variables as linear transformations
1.8 Rules for computing derivatives
1.9 The mean value theorem and criteria for differentiability
1.10 Review exercises for chapter 1
CHAPTER 2 SOLVING EQUATIONS
2.0 Introduction
2.1 The main algorithm: row reduction
2.2 Solving equations with row reduction
2.3 Matrix inverses and elementary matrices
2.4 Linear combinations, span, and linear independence
2.5 Kernels, images, and the dimension formula
2.6 Abstract vector spaces
2.7 Eigenvectors and eigenvalues
2.8 Newton's method
2.9 Superconvergence
2.10 The inverse and implicit function theorems
2.11 Review exercises for chapter 2
CHAPTER 3 MANIFOLDS, TAYLOR POLYNOMIALS,QUADRATIC FORMS,AND CURVATURE
3.0 Introduction
3.1 Manifolds
3.2 Tangent spaces
3.3 Taylor polynomials in several variables
3.4 Rules for computing Taylor polynomials
3.5 Quadratic forms
3.6 Classifying critical points of functions
3.7 Constrained critical points and Lagrange multipliers
3.8 Geometry of curves and surfaces
3.9 Review exercises for chapter 3
CHAPTER 4 INTEGRATION
4.0 Introduction
4.1 Defining the integral
4.2 Probability and centers of gravity
4.3 What functions can be integrated?
4.4 Measure zero
4.5 Fubini's theorem and iterated integrals
4.6 Numerical methods of integration
4.7 Other pavings
4.8 Determinants
4.9 Volumes and determinants
4.10 The change of variables formula
4.11 Lebesgue integrals
4.12 Review exercises for chapter 4
CHAPTER 5 VOLUMES OF MANIFOLDS
5.0 Introduction
5.1 Parallelograms and their volumes
5.2 Parametrizations
5.3 Computing volumes of manifolds
5.4 Integration and curvature
5.5 Fractals and fractional dimension
5.6 Review exercises for chapter 5
CHAPTER 6 FORMS AND VECTOR CALCULUS
6.0 Introduction
6.1 Forms on Rn
6.2 Integrating form fields over parametrized domains
6.3 Orientation of manifolds
6.4 Integrating forms over oriented manifolds
6.5 Forms in the language of vector calculus
6.6 Boundary orientation
6.7 The exterior derivative
6.8 Grad, curl, div, and all that
6.9 Electromagnetism
6.10 The generalized Stokes's theorem
6.11 The integral theorems of vector calculus
6.12 Potentials
6.13 Review exercises for chapter 6
APPENDIX: ANALYSIS
A.0 Introduction
A.1 Arithmetic of real numbers
A.2 Cubic and quartic equations
A.3 Two results in topology: nested compact sets and Heine-Borel
A.4 Proof of the chain rule
A.5 Proof of Kantorovich's theorem
A.6 Proof of lemma 2.9.5 (superconvergence)
A.7 Proof of differentiability of the inverse function
A.8 Proof of the implicit function theorem
A.9 Proving equality of crossed partials
A.10 Functions with many vanishing partial derivatives
A.11 Proving rules for Taylor polynomials; big O and little o
A.12 Taylor's theorem with remainder
A.13 Proving theorem 3.5.3 (completing squares)
A.14 Geometry of curves and surfaces: proofs
A.15 Stirling's formula and proof of the central limit theorem
A.16 Proving Fubini's theorem
A.17 Justifying the use of other pavings
A.18 Results concerning the determinant
A.19 Change of variables formula: a rigorous proof
A.20 Justifying volume 0
A.21 Lebesgue measure and proofs for Lebesgue integrals
A.22 Justifying the change of parametrization
A.23 Computing the exterior derivative
A.24 The pullback
A.25 Proving Stokes's theorem
BIBLIOGRAPHY
PHOTO CREDITS
INDEX
· · · · · · (收起)

具體描述

用戶評價

評分

##勘誤:http://matrixeditions.com/errata.html

評分

綫性方程是高斯算法,而非綫性問題是牛頓算法,牛頓算法在隱函數定理和逆函數定理證明中比較Picard迭代收斂更快

評分

綫性方程是高斯算法,而非綫性問題是牛頓算法,牛頓算法在隱函數定理和逆函數定理證明中比較Picard迭代收斂更快

評分

綫性方程是高斯算法,而非綫性問題是牛頓算法,牛頓算法在隱函數定理和逆函數定理證明中比較Picard迭代收斂更快

評分

綫性方程是高斯算法,而非綫性問題是牛頓算法,牛頓算法在隱函數定理和逆函數定理證明中比較Picard迭代收斂更快

評分

##勘誤:http://matrixeditions.com/errata.html

評分

綫性方程是高斯算法,而非綫性問題是牛頓算法,牛頓算法在隱函數定理和逆函數定理證明中比較Picard迭代收斂更快

評分

##勘誤:http://matrixeditions.com/errata.html

評分

##勘誤:http://matrixeditions.com/errata.html

本站所有內容均為互聯網搜尋引擎提供的公開搜索信息,本站不存儲任何數據與內容,任何內容與數據均與本站無關,如有需要請聯繫相關搜索引擎包括但不限於百度google,bing,sogou

© 2025 book.teaonline.club All Rights Reserved. 圖書大百科 版權所有